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A Unified Framework of Latent Feature Learning in Social Media

文献类型：期刊论文

作者Yuan, Zhaoquan1; Sang, Jitao1; Xu, Changsheng1; Liu, Yan2
刊名IEEE TRANSACTIONS ON MULTIMEDIA
出版日期2014-10-01
卷号16期号:6页码:1624-1635
关键词Deep learning feature learning india buffet process social media
英文摘要The current trend in social media analysis and application is to use the pre-defined features and devoted to the later model development modules to meet the end tasks. Representation learning has been a fundamental problem in machine learning, and widely recognized as critical to the performance of end tasks. In this paper, we provide evidence that specially learned features will addresses the diverse, heterogeneous, and collective characteristics of social media data. Therefore, we propose to transfer the focus from the model development to latent feature learning, and present a unified framework of latent feature learning on social media. To address the noisy, diverse, heterogeneous, and interconnected characteristics of social media data, the popular deep learning is employed due to its excellent abstract abilities. In particular, we instantiate the proposed framework by (1) designing a novel relational generative deep learning model to solve the social media link analysis task, and (2) developing a multimodal deep learning to lambda rank model towards the social image retrieval task. We show that the derived latent features lead to improvement in both of the social media tasks.
WOS标题词Science & Technology ; Technology
类目[WOS]Computer Science, Information Systems ; Computer Science, Software Engineering ; Telecommunications
研究领域[WOS]Computer Science ; Telecommunications
关键词[WOS]LINK-PREDICTION ; IMAGE RETRIEVAL ; NEURAL-NETWORKS ; ALGORITHM ; RELEVANCE ; MODEL
收录类别SCI
语种英语
WOS记录号WOS:000344720200011
源URL[http://ir.ia.ac.cn/handle/173211/2847]  
专题自动化研究所_模式识别国家重点实验室_多媒体计算与图形学团队
作者单位1.Chinese Acad Sci, Inst Automat, Natl Lab Pattern Recognit, Beijing 100190, Peoples R China
2.Hong Kong Polytech Univ, Dept Comp, Kowloon 999077, Hong Kong, Peoples R China
推荐引用方式
GB/T 7714		 Yuan, Zhaoquan,Sang, Jitao,Xu, Changsheng,et al. A Unified Framework of Latent Feature Learning in Social Media[J]. IEEE TRANSACTIONS ON MULTIMEDIA,2014,16(6):1624-1635.
APA Yuan, Zhaoquan,Sang, Jitao,Xu, Changsheng,&Liu, Yan.(2014).A Unified Framework of Latent Feature Learning in Social Media.IEEE TRANSACTIONS ON MULTIMEDIA,16(6),1624-1635.
MLA Yuan, Zhaoquan,et al."A Unified Framework of Latent Feature Learning in Social Media".IEEE TRANSACTIONS ON MULTIMEDIA 16.6(2014):1624-1635.

入库方式： OAI收割

来源：自动化研究所

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